Carbon4 Finance - BIODIVERSITY IMPACT ANALYTICS POWERED BY THE GLOBAL BIODIVERSITY SCORE™ (BIA-GBS) for the biodiversity impact and dependencies of companies
Data category
- Environmental data
- Indices/Exchange data
- Rankings
- Ratings
- Research data
- Verification/Certification/External opinion
- Dependencies data
The data offers solutions for:
- Carbon footprinting
- Climate scenario analysis
- Environmental impact analysis and insight
- Geospatial/location data
- Investment decisions and portfolio insight
- Nature-based information
- Nature-based information: Biodiversity
- Nature-based information: Land use
- Nature-based information: Water
- Norms-based screening
- Physical risk
- Reporting: CSRD
- Reporting: EU Regulations
- Reporting: Impact
- Reporting: SFDR
- Reporting: TCFD
- Reporting: TNFD
- Reporting: UN SDGs
- Temperature alignment
- Transition plan assessments
Who are the data users?
- Corporates
- Financial institutions
- Government
- Investors
- Trustees
- NGO; Schools; Banks; Index providers
Brief description of the data offering
BIA-GBS™ is one of the first databases able to provide a biodiversity footprint and a dependency score at a portfolio level and, therefore, to provide indicators for measuring physical and transition risk exposure:
- for 163 sectors, 44 countries and five ‘rest of the world’ macro-regions.
- for corporate equity instruments and corporate and sovereign debt instruments, with a total coverage of 7,200 issuers and 330,000 instruments.
- for the most material spots in the value chain - Scope 1, 2, and 3 - and for both terrestrial and aquatic freshwater ecosystems.
Our data is accessible through our platform and SFTP flux. We provide an unlimited number of users to our clients. Our platform works with Excel import/export and provides portfolio aggregation.
The following section provides a brief summary of the key indicators that are provided by BIA-GBS™.
- Absolute biodiversity impacts: BIA-GBS™ provides impact measures for entities and portfolios, aggregated on multiple levels:
- by biodiversity realm (terrestrial and aquatic impacts)
- by pressure (e.g. land use, climate change, encroachment, fragmentation, land use, atmospheric nitrogen deposition, wetland conversion, hydrological disturbance due to climate change, freshwater eutrophication, land use in wetland catchments, land use in river catchments)
- by accounting category (static and dynamic impacts) – investors can draw different lessons from looking at static (accumulated impacts over time) and dynamic (periodic gains and losses) impacts.
- by value chain Scopes (Scope 1, 2 and 3) – indirect impacts (categorised as Scope 3) are significant for most industries and need to be taken into account for a comprehensive, meaningful assessment of the biodiversity impact of companies.
- by sector (e.g., manufacturing of food products, extraction of petroleum products, etc.) – providing impacts by sectors can help to identify biodiversity impact hotspots of companies and portfolios and can serve as a basis for stakeholder engagement.
- Attribution and impact intensities: The attribution intensity (per amount invested) of an investment portfolio is an indicator that can be used to easily compare an investment portfolio to a selected benchmark. To compare a given company with its peers, the impact intensity per turnover is provided by BIA-GBS™. As for absolute impacts, attribution and impact intensities are available on different levels of aggregation.
- Two biodiversity dependency scores: these indicators, expressed as a percentage, indicate the dependency of an entity on different ecosystem services. As activities that are beyond the operational boundaries of a company, but still part of its value chain, are crucial to a company’s business, it is essential to account for direct (Scope 1), as well as indirect dependencies (Scope 3). We offer two ways to apprehend the dependency of companies on ecosystem services, both of them by calculating a score ranging from 0% (no known dependency) to 100% (very high dependency):
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- Average dependency score: The average dependency score measures the average dependency of the company, on its Scope 1 & Scope 3, for all the ecosystem services on its concerned activities. A drawback of this approach is that it might hide dependency on one or more ecosystem services and send a mixed signal, or be quite difficult to interpret. Indeed, being critically dependent on one ecosystem service might not appear in an average score if dependency on all other ecosystem services is low.
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- Critical dependency score: This score will depend on the critical exposure of one or more activities to one or more ecosystem services, closer to a boolean or “red flag” approach.
Where and how do you source your data?
The BIA-GBS™ database provides biodiversity footprint assessments computed using GBS, which expresses an entity’s impacts on biodiversity in MSA.km2. MSA stands for Mean Species Abundance and is expressed as a percentage. It is an indicator of the integrity of a given ecosystem, obtained by comparing this ecosystem to its pristine, undisturbed state.
BIA-GBS™ enhances the GBS base results with specific entity data provided by Carbon4 Finance: the core structure of the GBS and how it assesses the company's biodiversity footprint, as well as how Carbon4 Finance’s data is integrated.
Carbon4 Finance assesses the carbon footprint, physical risk and biodiversity impact on the complete value chain based on public information and public reports. C4 Finance collects physical and activity data, converts it into tCO2eq thanks to our emission factors developed by Carbone 4 expertise and calculates Scope 1 & 2 and Scope 3 emissions.
STEP 1 - ECONOMIC ACTIVITIES: Carbon4 Finance provides the mapping between the entities and its instrument’s identifier (ISIN), as well as the breakdown of companies’ revenues by sector of activity and by geographic location (mostly countries). The data comes from the CRIS (Climate Risk Impact Screening) database, a methodology developed by Carbon4 Finance to analyse a portfolio's exposure to physical climate risks.
STEP 2 - PHYSICAL INVENTORIES: EXIOBASE is an Environmentally Extended, Multi-Regional Input-Output Model (EEMRIO), indicating the economic and physical interdependencies between economic sectors and geographical regions. It is used to map the value chain of economic activities and translate sector and country-specific revenue data into inventories, which are physical amounts of materials and flows necessary to perform the company’s activities (including GHG emissions and water usage, for example). Hence, BIA-GBS™ considers the whole upstream value chain of companies in its biodiversity impact analysis.
Data from the CIA (Carbon Impact Analysis) database - developed and maintained by Carbon4 Finance, which provides companies’ GHG emissions on all Scopes (including Upstream and Downstream Scope 3 emissions), based on a comprehensive bottom-up analysis – is used to replace statistical GHG emissions derived from EXIOBASE, thus delivering a refined impact assessment.
STEP 3 - BIODIVERSITY PRESSURES: In-house tools developed by CDC Biodiversité estimate each physical flow’s contribution to biodiversity pressures, as defined by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). BIA-GBS™ encompasses the four macro-pressures broken down into 11 GBS pressures, but contrary to GBS, the contribution to ecotoxicity within the macro-pressure pollution is not assessed, as calculation still needs to be enhanced.
STEP 4 - IMPACTS: By using the GLOBIO model and its pressure-impact relationships, the GBS translates each pressure into impacts on ecosystem integrity, expressed in MSA.km2. Results are then normalised.
Finaly, companies’ risk exposure to the degradation of ecosystem services is assessed by BIA-GBS™ through a dependency score. It measures the direct and indirect dependencies on ecosystem services over the companys' whole supply chain (Scope 1 and Upstream Scope 3).
The BIA-GBS model provides two different dependency score: an average dependency score and a critical dependency score. It expresses the extent to which a company depends on a service provided by nature, known as an ecosystem service. The dependency scores are based on the ENCORE database, to which we add Scope 3.
We offer two ways to apprehend the dependency of companies on ecosystem services, both of them by calculating a score ranging from 0% (no known dependency) to 100% (very high dependency):
- Average dependency score: The average dependency score measures the average dependency of the company, on its Scope 1 & Scope 3, in average for all the ecosystem services on its concerned activities. A drawback of this approach is that it might hide dependency on one or more ecosystem services and send a mixed signal or be quite difficult to interpret. Indeed, being critically dependent on one ecosystem service might not appear in an average score if dependency on all other ecosystem services is low.
- Critical dependency score: This score will depend on the critical exposure of one or more activities to one or more ecosystem services, closer to a boolean or “red flag” approach.
What is the cost for your data offering?
Our suscription costs are discussed according to our client's needs.
